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That however does not really matter, life expectancy is based on where you current live, as it determines which health-related conditions you face. From there we can take a look at the UK, though I am not sure whether there are detailed immigration-related records. However, there is Scottish data (Gruer et al. Epidemiol Community Health 2016;70:1251-1254.) illustrates that. They found that life expectancy for White Scottish and mixed men is shorter to Indian, Pakistani or Chinese folks. Non-Scottish white British folks were a fair bit higher than Scottish, but still lower than the above mentioned. For women, White Scottish and White British were again lower than the above mentioned groups. Now, obviously it is not clear when folks with Indian, Pakistani or Chinese ethnicity actually immigrated. But in aggregate it provides evidence that immigration is unlikely to skew life expectancy data (the impact of Scottish folks on UK data would be much higher, whereas immigrant data would have either no or a slight positive effect, considering population size). Considering that the proportion of first generation immigrants at any time is fairly low, that is unlikely to affect LE as a whole. That being said, socio-economic status are associated with health status, and assuming an overrepresentation of immigrants in low-skilled jobs could lower their life expectancy (though again, in the case of Scotland, other factors have a much stronger effect, though internal migration is something that should also be checked). However, it does not automatically mean that immigration is (or can be) a driver of lower life expectation. The reason being that even if all immigrants suddenly vanish, there will still be low skilled labour jobs and socioeconomic disparities (in fact, there is evidence that with a contracting economy, such as by removing part of the population, these issues would be amplified). In other words, lower health outcomes would then be shifted toward the native population and thereby not increase overall life expectancy. I think it is fair to say that ad hoc determination of such complicated measures are not trivial (or likely to be accurate) and as such it is almost impossible to extrapolate without thorough statistical analyses (and even then models may miss out important parameters).

Many of the additional deaths in the UK were in the older population, i.e. those that were likely to have smoked for a long while. Among younger folks, drug use and related incidents appear to be a major factor. With regard to diet, some studies suggest that recent immigrants eat healthier, though once they get accustomed to their host country diet (For Canada and UK there is data) the nutritional quality of the diet declines. Specifically for the UK it should also be mentioned that on average immigrants to the UK are, on average, healthier than their British counterparts (data is based on various Labour Force Surveys and subsequent analyses based on that data) . This is a phenomenon that some have termed the "migrant health advantage". For the most part it is because mostly healthy folks immigrate (which of course is not true for asylum seekers, which usually suffer from low health). Once getting older, this advantage diminishes, depending on the group of immigrant and the level of heavy labour. For example, above 65 most immigrants from EU and SE asia reprt less issues than their British counterparts, whereas East European and Pakistani immigrants had more issues. However, when taking skill level into account, all age groups of immigrants reported less health issues than their UK born counter-part. In fact, the levels of health issues in low skilled immigrants is about that of high-skilled UK born folks, except for the highest age bracket where it is similar to medium-low skilled UK-born workers. There is also data regarding smoking, showing that in men only immigrants from India and Sub-Saharan Africa are smoking less than UK-born folks (the highest rate is found in East European immigrants), whereas in women only the East European group smoked more than UK-born women.

There are, though different countries collect different health information which sometimes makes direct comparison a bit iffy. I would also like to note that seemingly the article is using slightly different measures in a somewhat jumbled way. Also, it should be noted that there is a limit what we can theoretical achieve in life-span so at some point it is expected to just fluctuate rather than increase. That being said, looking at comparative data, the UK, falls behind other OECD countries, but the UK is consistently at the bottom. Taking 2015 (where there is harmonized OECD data allowing direct comparison) the female life expectancy was for example 81.47 in the US, 82.72 UK, 82.98 Germany, 84.01 Canada with Japan having the highest (87.02) and the average being 84.17. the male values are (same order): 76.5, 79.05, 78.13, 79,93, 80.78, average: 79.48. In the US, there have been analyses showing that especially African Americans had an extreme low life expectancy, though in recent years that gap has become narrower. Unfortunately it is only partially due to lower mortality, another part is an increasing white mortality. However, most OECD countries experienced life expectancy decline around that time (though e.g. Canada and Australia did not experience that). However, there are different patterns. In the US, the decline was driven by increased mortality in folks younger than 65, whereas in most other countries it was driven by mortality increase in the older part of the population. In the latter group, cardiovascular and respiratory diseases (including flu) explained most of the pattern. In the US, drug-related deaths played a major role (especially for men), as well as influenza-related deaths (there were a number of serious outbreaks).

I should note that the timing would still be off as the split gray wolf and the ancestor of the dog (which would be the common ancestor of extant wolves and dogs in the usual definition) is earlier than the the evidence for domestication and is conservatively estimated to happen at least 27k years ago. I.e. about 9k years before the puppy lived. However, since the pup was found roughly around the time of divergence/domestication it would could be part of an admixing population (but not be part of the ancestor population in the common sense), if that makes sense.

I think I may know the studies that could have been referred to. The issue was that during earlier studies the above mentioned earlier dates of dog ancestry were discussed, based on e.g. analyses of the Altai canine from ca. 30k years ago. However, subsequently more mitochondrial DNA from wolves were sequenced which questioned the validity of those analyses somewhat (or at least this was a hotly discussed issue a while back). However, it is clear that Gray wolves date back to at least 70k years (more disputed record go back to 1 myr). What may have been discussed in this context is the split from ancestral (or modern) wolf lineages. For example, there is discussion that modern populations of gray wolves (and dogs) might have their origins in a single population. While the timing might still a bit off with 18k years (depending on the precise estimate of the origins of the dog, and geographic constraints) at least in theory it could be possible that the puppy was part of that ancestral population (again, we are talking below the species level here, the wolf lineage is much older). However, that should be testable and the fact that there is nothing noted about that makes me believe that the data is not there yet.

That is highly unlikely. While there are some issues with pinpointing when dogs became domesticated, the oldest assumptions would be ~30k ago, whereas more conservative ones placed it closer to 15k. Some of the issues are caused by interbreeding and the possibility of multiple domestication events (followed by interbreeding sometime later). In contrast, the ancestor of wolves are placed more than 750k years ago. The article itself does not really say what the issue is, but I have seen elsewhere (assuming it is recorded correctly) that they are trying to sequence its whole genome (rather than amplifying diagnostic markers). So far there was only a comment indicating as having only low coverage so far, which could mean that they have not covered the diagnostic areas yet and/or are still in the assembly process. Since whole genome sequencing requires higher quality in the specimen, it is also possible that they are running into quality issues.

Racism is a complicated and often misunderstood concept. However, specific to the 2016 electorate an increasing body of literature (I have referenced a number of those elsewhere) suggest that racial resentment, anti-immigrant sentiments and sexism are major predictors for Trump voters. That does not mean that all of them harbour racist tendencies, but it is a stronger indicator than other parameters typical for protest voters (such as distrust for politicians, dissatisfication with democracy) or economic hardship. A study from Mutz showed, for example that folks actually losing jobs or were impacted by stagnant wages were not the ones most likely to vote Trump. Rather, folks that felt under threat by social change (e.g. those that think that white folks are more discriminated against). The studies also imply that actual economic improvement will not change sentiments and indicates that the "left-behind-theory" most commonly presented by the media will not really address the needs of a significant size of the voters. Other studies also found that anti-establishment sentiments ("drain the swamp", hostility against "elites") While it does not mean that it is a third (or more or less) of Trump voters, but it means that they are biggest coherent group driving the election for Republicans. There is of course a big chunk of partisanship voters, who will vote Republican regardless of the candidate, those may or may not fall into the above group, but certainly they are not sufficiently adverse to them, nor are they a viable group for recruitment for the opposing party, either. Thus, these sentiments are major drivers of elections , even if it may be considered distasteful to be discussed publicly, compared to other narratives. This poses a fundamental problem in politics as it there are likely only a limited number of ways to engage with these voters, which, as the stats show, were key to the 2016 election. One, is to pretend that these issues do not exist or engage in alternative narratives, such as the "left-behind" or "we are better" rhetoric (which to some degree seems to be the case with the Democratic party) and pretty much lose this voter potential. The basic idea is probably to split off those that vote Republicans for other reasons, but it is unclear whether that would be numerically relevant (or even possible). Another one is to engage and demonstrate overlapping values (which happened in 2016 and it appears to be even stronger in 2020 in the Republican party) and thereby capture that voter base. That is not really that new, it is more that at least overt anti-immigrant sentiments have been retreating from the Democratic party (which makes them unvotable for said part of the electorate). That has the advantage of not rallying the base, but also recruit otherwise Democratic voters which harbour similar sentiments (a bit of that was observed also under Obama). There are indeed papers looking into vote switching and found that in that group again, racial and immigration attitudes were the key factors (Reny et al. Pub Op Quart, 2019 83:1) and that these attitudes sort White voters into increasingly polarized groups. However, Democrats cannot (luckily?) play the same game, as they would then more likely lose a significant chunk of minority voters, which have become a crucial voter base for them. In other words, playing up racial sentiments are a win-win game for Republicans and lose-lose for Democrats (even mentioning racism in whatever context is often enough to shore up resentment). This, incidentally, is a sentiment that Bannon picked up and tries to sell hard as election strategy (not only in the US, but also in Europe, where we see similar mechanisms at play).

Oh, it is questioned for sure, though much of it is within the scientific communities. Many are aware that when it comes to medicine we are often using sledgehammers to address very delicate questions. Reasons range from knowledge gaps to technical challenges. However, what trickles out usually lacks nuance with sometimes fatal consequences. The thing is that if folks overestimate the things we understand it creates unfounded trust, but realistically there is often not a lot of alternatives. On the other hand skeptics may just abandon the little we actually know and go full crazy (such as anti-vaccination movements).

Oh no, there are huge repositories that you can freely access so that is generally not an issue. Even if your specific species is missing you can at least take the closes assumed relatives and work from there. Also, when you sequence something new and publish it, you have to make to submit it to one of those public databases.

As briefly mentioned, it all depends on what type of analysis is being conducted. If for example we use a species-specific marker that is not found in the species under investigation, we would not be able to amplify anything, resulting in basically no result. Similarly, DNA can degrade or be contaminated to such a degree that we will not obtain data, either. However, if the DNA is of sufficient quality to be amplified, either restriction analyses or sequencing will allow you to assess relationship to known species via phylogenetic reconstruction. There is a paper by Sykes et al. (Proc Royal Soc. B, 2014 281:1789) in which they analysed hair samples which were attributed to e.g. Yetis or similar organisms. After thorough de-contamination they sequenced a part of the mitochondrial DNA and found that they were actually from a wide range of mammals. Samples attributed to bigfoot were found to be cow, coyote, deer, black bear, horse, racoon and human, respectively. Two samples matched a fossil record related to current polar bears.

I find that to be a rather important point. According to some reports the suspected weight of the stainless steel body (and added cost) and the requirement of a rather large battery. Not sure how true that is, but there is at least one article casting doubt of it hitting all the numbers as well as cost.

Yes, unfortunately. As a whole they are well preserved allowing certain in-vitro analyses. The problem is that the damage is on the (sub)-cellular level. Even fresh samples do see a certain level of degradation, if not carefully prepared.

It is very difficult to clone something if you do not have intact cells. Earlier this year the group from Iritani (Kindai University) have isolated nuclei from frozen mammoth samples and introduced them into mice egg cells. While some activity was observed the damage was too great as a whole.

The timeline would fit with an early domesticated wolf/dog. Though of course there is also a high likelihood of ongoing interbreeding which could make it more difficult to define a clear distinction.

So species identification is a very specific application and there have been techniques developed based on hair-snaring. A typical genetic target are conserved mitochondrial sequences, which can be obtained from hair samples even with few or no follicles attached (though yield is better if one gets more cells with them). In the past one would do restriction analyses (in short: amplify region with PCR, digest the amplified DNA sequence and look at the resulting pattern to compare with known species), though more commonly nowadays the amplified locus is sequenced and compared to a reference database (often also called DNA-barcoding). Even if the sequence is not found, one can use conserved sequences to build a so-called phylogenetic tree. There, the sequence in question would be quantitatively compared to existing ones and based on similarities one could figure out how the unknown species is related to known ones (i.e. if it is a close relative, for example). As long as a conserved locus is used (such as e.g. cytochrome C oxidase you will always get relationship info (i.e. it would not return as unknown). One issue could be contamination by other species, but as long as you can get some clean reads out of the sample of interest, it is often possible to isolate the novel from contaminating ones. That is a part of the problem, many TV shows, especially those who are more sensationalist usually do not care much about proper reporting. There is a decent chance that a) all they got is something mundane, such as regular wildlife and reporting it as unknown just sounds more exciting, b) they contaminated their samples and mostly got DNA from their producer who handled the samples inadequately but did not have the budget to repeat the whole thing or c) they got data, but did not bother to ask an expert to interpret it or d) they used a different method, but would require some elaboration.

Essentially there are a range of DNA tests in use. To test familial relationships for example one can amplify certain DNA regions of DNA and compare them to references e.g. from the parents. If you submitted a different species, you obviously would not get usable results. In other words, the type of DNA tests are highly specific, depending on purpose and will have to be designed differently for each application as well as species. I should also note that the vast majority of these test are not based on sequencing, but mostly rely on a form of genotyping. I.e. one monitors genetic variation at a given chromosomal location.

In addition to what others said, you can get mitochondrial DNA from hair; it depends on what types of analyses you want to run.. It depends on the type of assay. The vast majority of DNA testing is performed on diagnostic regions and comparison with reference data sets. But the actual loci as well as the database being used would define what you can or cannot identify. The description does not provide enough information.

Indeed. Also, it is a matter of specialization, climate change impacts a variety of disciplines ranging from physics to ecology. Other questions have a narrower range of disciplines with applicable research interests and expertise. Criticizing scientists for working within their field of expertise seems misplaced. In addition, there are many more challenges which some may find more urgent (I worry a lot about non-treatable infections, for example), but I personally would not go around and dismiss other urgent issues as noise.

! Moderator Note Considering the direction of the discussion, this has been moved to Philosophy.

But of course that is not the argument that you made. Here you claim that a no-change model is by default better than an accelerated timeline. I would concede that predicting the trend alone may be way off, but I was thinking within constraints that you provided (in this cause moderately off, rather than extreme unrealistic values).

That is not how models generally work. The accuracy of a model is not contingent on just having somehow all possible parameters in them, but rather to accurately model (and ideally predict) what the interplay of these factors cause. A no-change model obviously fails to capture important mechanism that actually lead to (the observed) increase in temperature. As such it useless as it is unable to even predict the rough trend. Meanwhile, model predicting trends but getting the rate wrong at least got the trend correctly, but may not be fine enough to get the rates correct. An analogy is perhaps if you are sick and have a fever and one diagnosis claims that you are actually healthy and the other diagnoses some disease but is unable to suggest which bug you actually have. The latter carries more information than the former and coincides better with available data.

Well green tea generally should have a yellow to brown colour but if you are using crushed leafes in tea bags (which I feel should also banned for green tea) they can extract much faster than loose leafs.

I'd argue the opposite. "No change" is not a baseline or default. It is specific model indicating a type of steady-state situation. Trends up or downwards indicate deviations from it. Thus, if you capture the trend but get the rate wrong it still means that you have captured more mechanisms at work moving away from the stable assumptions (but may be missing or underestimating some elements) compared to a model which predicts no change. Surprise! Quite a few do, actually. I may be misremembering, but I am fairly sure that in the early 90s/late 80s a consensus in the scientific community has formed regarding climate change (wasn't IPCC established around that time)? Obviously some would have been careful about making predictions, but I vaguely remember some being fairly outspoken on that matter back then. After all, it generated enough momentum for the Kyoto protocol, which, considering the power of the opposition, indicates that the science of that time created enough momentum to get politics moving (which is always an astonishing feat). The big issue is that that this type of skepticism denies science and as such there are no valid counter arguments. If folks already decide on what they want to believe there is not a lot of ways to dissuade them. It used to be possible to demonstrate e.g. that their arguments were sponsored by the industrial PR groups. But now these beliefs are so tightly integrated into their political identity, that this would only be perceived as an attack against them, rather than the arguments.

I think that is an excellent point and as per my above post, to my knowledge the connection is unclear and may very well be unspecific (assuming it exists in the first place outside of in vitro experiments). As such I suggest that the thread goes back to discussing the fundamentals of the question asked in OP rather than introducing highly speculative evolutionary anecdotes. The only things I would like to add is that it is obviously that adaptations in humans precede the time before they were considered a new species (or in other words, we need to look at least at hominins as a whole) and at the same time minor adaptation can occur in a relatively short amount of time (such as Strange pointed out). Examples include differences in shivering responses or vasoconstriction in different populations. In addition, one hypothesis regarding human evolution is that they evolved in a time when climate patterns were unstable with decreasing temperatures and humidity. The variability selection hypothesis (championed by Potts) then states that hominin evolution is not an adaptation to a particular set of environmental parameters, but instead is shaped by the instability itself. That would explain the variability of the human species (and implicitly it also shows that evolutionary narratives of human behaviour are often"just-so" narratives as the latter typically rely on a defined set of selective pressures to have any kind of predictive powers). Edit: I realized that I may have veered off to far from my original point, but the response is more meant to indicate that grand evolutionary narratives are unlikely able to address OP and we would rather need to focus on direct evidence linking temperature to immune responses, if we can find them.

Well it may (or may not) surprise you but climate change research has been subject to political scrutiny. During the Harper years in Canada, for example long-standing research projects which have collected valuable data have seen severed cuts and some programs were essentially halted. The Trudeau government has since then reversed some of those decisions, but there are still many projects being in danger of being shut down. The fatal thing about many of these projects is that in order to provide good data they need to collect samples on a regular basis. Funding gaps result in data gaps which in turn result in poor quality models. In the US, the current government also has cut funds to project initiated earlier (as well as withdrawn funds to finance global climate change-related projects). Most researchers that I know in that field mention that there is a certain urgency within the community and peer reviewers for these types of studies are often positive (if one comes up with reasonable ideas). However, big calls specifically targeting those challenges are not in line with the data gaps we still have. That being said, it is difficult to track the dollars in detail, as not all related research are labelled as climate change-related projects. For example, a study may study the change in insect population, or forest ecology and eventually come to the conclusion that changes in weather patterns are the main drivers. While the study is not specifically looking at the effects of climate change, it may nonetheless provide important insights.